title: When less is more: a simple predictive model for repeated prostate biopsy outcomes.
abstract: OBJECTIVE
  To present a new predictive model for repeated prostate biopsy outcomes. Several practical problems are described that arise when searching for a proper model among those that already exist. A new model is developed with only two explanatory variables and a simple graphical output.
  
  
  METHODS
  This is a retrospective cohort study based on data collected from December 2006 to June 2011 at the Clinic of Urology of the University Hospital in Olomouc, Czech Republic. The cohort consists of 221 patients who underwent the first repeated biopsy after an initial biopsy with a negative outcome. All patients had prostate-specific antigen (PSA) levels between 1.5 and 16.5 ng/mL and a prostate volume not greater than 100mL. A logistic regression model was fitted.
  
  
  RESULTS
  Of the 221 patients, 29 (13%) were diagnosed with prostate cancer on the repeated biopsy. The final model includes the PSA level and the transitory zone volume as predictors. Its accuracy is 76.4%. The cut-off point of 0.0687 in the predicted positive repeated biopsy outcome assures 95% sensitivity and prevents 42% of unnecessary biopsies.
  
  
  CONCLUSIONS
  The accuracy of the model is comparable to that of more complex models (with more than two predictors) published in the literature. The model includes only two routinely measured variables, and hence it is accessible for a wide range of practitioners. The simple graphical outcome makes the model even more attractive.
authors.affiliation: Dpt. Mathematical Analysis and Applications of Mathematics, Faculty of Science, Palacky University in Olomouc, 17. listopadu 12, 772 00 Olomouc, Czech Republic. Electronic address: ondrej.vencalek@upol.cz.
authors.forename: Ondrej
authors.initials: O
authors.lastname: Vencalek
authors.forename: Kamila
authors.initials: K
authors.lastname: Facevicova
authors.forename: Tomas
authors.initials: T
authors.lastname: Furst
authors.forename: Michal
authors.initials: M
authors.lastname: Grepl
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001707:Biopsy, Needle; D018153:Czech Republic; D003661:Decision Support Techniques; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000601:surgery; D012189:Retrospective Studies
chemical_list: D017430:Prostate-Specific Antigen
keywords: Nomogram; Prostate cancer; Prostate-specific antigen; Repeated biopsy; Transitory zone